Energy Regeneration of Active Suspension System in Fuel Cell Vehicles
Bibliographic record
Abstract
Active suspension (AS) system is primarily responsible for vehicles’ ride quality and safety enhancement. However, the high power demand and fast dynamics of this system confine its application in conventional vehicles. Fuel cell hybrid electric vehicles (FCHEVs) are local zero-emission HEVs with a promising perspective in the transportation section and, due to their comprehensive energy storage system (ESS), can well supply the AS’s power demand. Although AS load can increase fuel consumption and limit the driving range of FCHEVs, the energy regeneration of the AS system may compensate for this augmented fuel consumption and even contribute to further fuel economy. A regenerative AS system is proposed for a passenger FCHEV. The AS system comprises four independent regenerative fuzzy AS systems. The ESS is a combined battery/ultracapacitor system responsible for powering the AS system and capturing the regenerated energy based on the proposed energy regeneration scheme. The energy management system (EMS) is also a central fuzzy logic controller (FLC) that determines the power split between the power sources. Simulation results reveal that the AS load increases fuel consumption and accelerates ESS degradation. However, regeneration of the AS load can effectively improve fuel economy and FC aging.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".